Algorithms that can analyze the microbiome after diet induced changes

An increasing body of evidence supports that the gut microbiome composition can alter host metabolism, and eventually result in disease.  To date most of these studies have pointed to associations between the microbiota and host metabolism, but little has been able to demonstrate causal relationships between the two.  To address this, researchers from Sweden developed a specialized computational platform called CASINO (Community and System-level Interactive Optimization) to quantify the release and consumption of metabolites from gut microbiota, and pairing this data to dietary intake characteristics and patterns.  CASINO in a multidimensional platform, but ties both species richness/diversity to dietary intake in the gut microbiome.  The algorithms were optimized to distinguish bacteria that consumed carbohydrates/metabolites, and those that produce metabolites instead. 

In an in vitro validation test, the CASINO simulation was able to predict net production of metabolites produced by each community and was even able to distinguish between the syntheses of more essential amino acids as compared to non-essential amino acids.  In the past, researchers have been able to link two to three species to metabolic consumption rates.  Using CASINO, researchers in this study were able to write algorithms that could analyze at least five species.  The analysis quantified the contribution of individual bacteria to the overall microbiome, as it was shown that B. thetaiotaomicron, E. rectale, and F. prausnitzii dominated metabolism. 

CASINO was also used in a clinical experiment.  Data was examined from an experiment in which 45 overweight and obese individuals were given a restricted low-calorie diet for 6 weeks.  The simulation was able to characterize species diversity and composition.  After characterizing the species, CASINO was also used to simulate the effect of diet on the gut microbiome composition at baseline and after diet intervention in the test subjects.  CASINO algorithms were able to predict a decrease in carbohydrate consumption and increase in amino acid consumption (i.e. protein) by analysis of microbiota metabolites of the five select gut bacterial species. 

The CASINO algorithms examined most metabolic functions and allowed several species to be included in a simulation.  Furthermore, the authors propose that the program is scalable to include more than five species.  CASINO could pave the way toward development of quantification methods that could serve as a predictive interaction tool, especially in light of the importance of biomarkers in predicting disease onset.  We discussed biomarkers last week in our blog regarding renal disease, and these types of tools could provide exceptional value for clinical diagnostics.

Stool consistency should be considered during microbiome research

Stool sampling remains the most common method of measuring the microbiome of the GI tract.  Researchers are well aware of its limitations, but its ease and convenience for both scientists and donors makes it nearly irreplaceable at the moment.  The most common issue regarding stool samples that is often pointed out is that it is not representative of the GI tract, and that it only samples the lower colon and not the more proximal GI tract.  In addition, it does not account for bugs that are attached to the mucous linings of the intestine rather than those that transiently pass with our feces.  Related to this point, last week Jack Gilbert and John Alverdy, professors from the University of Chicago, published a piece in the journal Gut regarding stool microbiome sampling and stool consistency.

Professors Gilbert and Alverdy argue that stool consistency greatly affects the stool microbiome populations.  The stool consistency is normally a function of intestinal transit time, with the shorter the duration between eating and passing stool being associated with watery stool, while a longer duration is associated with a more solid stool.  They point to studies that that show different bacteria have evolved to either grow rapidly when the stool is quickly moving through the lumen, in order to proliferate with the shorter duration access to nutrients, or to grow slowly and more completely utilize the available nutrients when the stool is accessible for longer periods.  Measurements of stool consistency are hardly ever performed during normal sampling, and these same studies tend to make generalizations about different phyla, like Bacteroides and Ruminococcacea, when in fact these different can be explained by stool consistency. 

In a time where microbiome diagnostics are starting to be considered as helpful indications for varous diseases, this type of quality control needs to be established.  Stool sampling is not perfect, but it is necessary, and for that reason steps should be taken now to improve and control its usefulness, especially in a clinical setting. 

The microbiome of alcoholics may contribute to pathologies

We have written before about the microbiome’s association with alcoholism, and how it has been implicated in many of the maladies connected with the disease.  Recently, research out of George Mason University, published in PLoS ONE, explored the molecular mechanisms behind this relationship.   The scientists measured the metabolites that were formed by the microbiome of alcoholics and compared it to healthy controls.  They discovered that the metabolites that differed between the two groups have important implications on gut health.

The scientists measured the volatile molecules that were being effused from the feces of 18 healthy controls and 16 alcoholics.  The alcoholics’ feces contained high levels of an organic compound called tetradecane, which is known to cause oxidative stresses.  Increased oxidative stress in the gut, especially in alcoholics, is associated with increased gut permeability (i.e. leaky gut), and alcoholic steatohepatitis (i.e. a type of liver disease).  Moreover, specific fatty acids, which are known to reduce oxidative stress (antioxidants), were more depleted in alcoholics when compared with healthy controls.  In addition, the alcoholic feces consisted of lower abundances of short chained fatty acids (SCFAs), which are nearly always associated with intestinal health (click the SCFA tag below to learn more).  Finally, other molecules which are associated with health, like caryophyllene and camphene, were decreased in the guts of alcoholics.

Overall these results show the possible mechanisms by which the microbiome contributes to alcoholism.  Specifically, it appears that the alcoholic microbiome may create oxidative stress molecules, which contribute to gut toxicity.  In addition, the scientists suggest this work could be used as an alcoholism diagnostic, as the characteristic metabolites between the groups were statistically significant.